Mapping assays to the key characteristics of carcinogens to support decision-making.

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Gabrielle Rigutto, Cliona M McHale, Ettayapuram Ramaprasad Azhagiya Singam, Iemaan Rana, Luoping Zhang, Martyn T Smith
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引用次数: 0

Abstract

The key characteristics (KCs) of carcinogens are the properties common to known human carcinogens that can be used to search for, organize, and evaluate mechanistic data in support of hazard identification. A limiting factor in this approach is that relevant in vitro and in vivo assays, as well as corresponding biomarkers and endpoints, have been only partially documented for each of the 10 KCs (Smith MT, Guyton KZ, Kleinstreuer N et al. The key characteristics of carcinogens: relationship to the hallmarks of cancer, relevant biomarkers, and assays to measure them. Cancer Epidemiol Biomarkers Prev 2020;29:1887-903. https://doi.org/10.1158/1055-9965.EPI-19-1346). To address this limitation, a comprehensive database is described that catalogues these previously described methods and endpoints/biomarkers pertinent to the 10 KCs of carcinogens as well as those referenced as supporting evidence for each KC in the International Agency of Research on Cancer Monograph Volumes 112-131. Our comprehensive mapping of KCs to assays and endpoints can be used to facilitate mechanistic data searches, presents a useful tool for searching for assays and endpoints relevant to the 10 KCs, and can be used to create a roadmap for utilizing data to evaluate the strength of the evidence for each KC. The KC-Assay database is available to the public on the web at https://kcad.cchem.berkeley.edu and acts as a 'living document', with the ability to be updated and refined. Database URL: https://kcad.cchem.berkeley.edu.

对致癌物的关键特征进行制图分析,以支持决策。
致癌物的关键特征(KCs)是已知人类致癌物的共同特性,可用于搜索、组织和评估支持危害识别的机制数据。这种方法的一个限制因素是,相关的体外和体内试验,以及相应的生物标志物和终点,仅部分记录了10种KCs中的每一种(Smith MT, Guyton KZ, Kleinstreuer N等)。致癌物的主要特征:与癌症特征的关系,相关的生物标志物,以及测量它们的方法。癌症流行病学杂志,2020;29:1887-903。https://doi.org/10.1158/1055 - 9965. - epi - 19 - 1346)。为了解决这一限制,本文描述了一个综合数据库,该数据库将这些先前描述的与10种致癌物质相关的方法和终点/生物标志物以及国际癌症研究机构专著第112-131卷中作为每种致癌物质的支持证据的方法和终点/生物标志物进行了分类。我们全面的映射;化验和端点可以用来促进机械的数据搜索,提出了一种有用的工具,寻找相关化验和端点10;,,可以用来创建一个路线图利用数据来评估每个KC的证据的力量。KC-Assay数据库向公众提供在网络上https://kcad.cchem.berkeley.edu和充当“活文件”,能够被更新和改进。数据库地址:https://kcad.cchem.berkeley.edu。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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